Atzmueller, M. & Nalepa, G. J.: Towards Rapid Knowledge Capture using Textual Subgroup Mining for Rule Prototyping. In: Technical Report 458, Institute of Computer Science, University of Würzburg (2009),
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Atzmueller, M.; Puppe, F. & Buscher, H.-P.: Towards Knowledge-Intensive Subgroup Discovery. Proc. LWA 2004 Workshop, Germany. 2004, S. 117-123
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Atzmueller, M.; Baumeister, J.; Hemsing, A.; Richter, E.-J. & Puppe, F.: Subgroup Mining for Interactive Knowledge Refinement. Proc. 10th Conference on Artificial Intelligence in Medicine (AIME 05). 2005LNAI 3581 , S. 453-462
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Atzmueller, M.; Baumeister, J. & Puppe, F.: Semi-Automatic Learning of Simple Diagnostic Scores Utilizing Complexity Measures. In: Artificial Intelligence in Medicine. Special Issue on Intelligent Data Analysis in Medicine 37 (2006), Nr. 1, S. 19-30
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Atzmueller, M.; Baumeister, J. & Puppe, F.: Quality Measures for Semi-Automatic Learning of Simple Diagnostic Rule Bases. Proc. 15th Intl. Conference on Applications of Declarative Programming and Knowledge Management (INAP 2004). Potsdam, Germany: 2004, S. 203-213
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Atzmueller, M.; Puppe, F. & Buscher, H.-P.: Profiling Examiners using Intelligent Subgroup Mining. Proc. 10th International Workshop on Intelligent Data Analysis in Medicine and Pharmacology (IDAMAP-2005). Aberdeen, Scotland: 2005, S. 46-51
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Baumeister, J. & Atzmueller, M. (Hrsg.): Proceedings of the LWA 2008 - Lernen, Wissen, Adaptivität. Institute of Computer Science, University of Würzburg, 2008Technical report 448
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Atzmueller, M.: Knowledge-Intensive Subgroup Mining - Techniques for Automatic and Interactive Discovery. IOS Press, 2007 (Dissertations in Artificial Intelligence-Infix (Diski) 307)
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Atzmueller, M.; Baumeister, J. & Puppe, F.: Inductive Learning of Simple Diagnostic Scores. Medical Data Analysis, Proc. 4th Intl. Symposium on Medical Data Analysis (ISMDA 2003), LNCS 2868. 2003, S. 23-30
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Baumeister, J.; Atzmueller, M. & Puppe, F.: Inductive Learning for Case-Based Diagnosis with Multiple Faults. Advances in Case-Based Reasoning. 2002 (LNAI 2416), S. 28-42
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Atzmueller, M.; Puppe, F. & Buscher, H.-P.: Exploiting Background Knowledge for Knowledge-Intensive Subgroup Discovery. Proc. 19th International Joint Conference on Artificial Intelligence (IJCAI-05). Edinburgh, Scotland: 2005, S. 647-652
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Atzmueller, M.; Baumeister, J. & Puppe, F.: Evaluation of two Strategies for Case-Based Diagnosis handling Multiple Faults. Proc. 2nd Conf. Professional Knowledge Management (WM2003). Luzern, Switzerland: 2003
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Atzmueller, M.; Beer, S.; Hörnlein, A.; Melcher, R.; Lührs, H. & Puppe, F.: Design and Implementation of a Data Warehouse for Quality Management, System Evaluation and Knowledge Discovery in the Medical Domain. Proc. 1st European Workshop on Design, Evaluation and Refinement of Intelligent Systems. Erfurt: 2008
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Atzmueller, M. & Seipel, D.: Declarative Specification of Ontological Domain Knowledge for Descriptive Data Mining (Extended version). Proc. 18th International Conference on Applications of Declarative Programming and Knowledge Management, accepted. 2008
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Puppe, F.; Buscher, G.; Atzmueller, M.; Huettig, M. & Buscher, H.-P.: Clinical Experiences with a Knowledge-Based System in Sonography (SonoConsult). Professional Knowledge Management. 2005LNAI , S. 319–-329
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Atzmueller, M. & Seipel, D.: Causal Subgroup Analysis for Detecting Confounding (Extended version). Proc. 18th International Conference on Applications of Declarative Programming and Knowledge Management, accepted. 2008
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Atzmueller, M.; Shi, W.; Baumeister, J.; Puppe, F. & Barnden, J. A.: Case-Based Approaches for Diagnosing Multiple Disorders. In: Barr, V. & Markov, Z. (Hrsg.): Proc. 17th Intl. Florida Artificial Intelligence Research Society Conference 2004 (FLAIRS-2004). AAAI Press, 2004, S. 154-159
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Atzmueller, M. & Nalepa, G. J.: A Textual Subgroup Mining Approach for Rapid ARD+ Model Capture. Proc. 22nd International Florida Artificial Intelligence Research Society Conference (FLAIRS), accepted. 2009
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Atzmueller, M.; Puppe, F. & Buscher, H.-P.: A Semi-Automatic Approach for Confounding-Aware Subgroup Discovery. In: International Journal on Artificial Intelligence Tools (IJAIT) 18 (2009), Nr. 1, S. 1 - 18
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Atzmueller, M. & Puppe, F.: A Case-Based Approach for Characterization and Analysis of Subgroup Patterns. In: Journal of Applied Intelligence 28 (2008), Nr. 3, S. 210-221
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